Search

Dynamic multi-objective optimization problem (DMOP) is quite challenging and it dues to that there are multiple conflicting objects changing over with time or environment. In this paper, a novel cooperative coevolutionary dynamic multi-objective optimization algorithm (PNSCCDMO) is proposed. The main idea of a new cooperative coevolution based on non-dominated sorting is that it allows the decomposition process of the optimization problem according to the search space of decision variables, and each species subcomponents will cooperate to evolve for better solutions. This way derives from nature and can improve convergence significantly. A modified linear regression prediction strategy is used to make rapid response to the new changes in the environment. The effectiveness of PNSCCDMO is validated against various of DMOPs compared with the other four algorithms, and the experimental result indicates PNSCCDMO has a good capability to track the Pareto front as it is changed with time in dynamic environments. [ABSTRACT FROM AUTHOR]

Establishing a mathematical model that can reflect the relationship between temperature increase and thermal error during machining is the core of thermal error compensation technology for CNC machine tools. The collinearity between temperature-sensitive points and the correlation between temperature-sensitive points and thermal errors are important factors affecting the prediction accuracy and robustness of the thermal error compensation model. Based on the thermal error measurement experiments of the Leaderway-V450 CNC machine tool in different periods of the year, the principal component regression (PCR) modelling algorithm, which can eliminate the collinearity effect, is proposed to establish the thermal error compensation model of the machine tool on the basis of selecting the temperature-sensitive points by using the correlation coefficient. It is compared with the newly proposed ridge regression thermal error compensation modelling algorithm. The results show that the thermal error compensation modelling method proposed in this paper can basically control the Z-direction thermal error of the CNC machine tool spindle within 10 μm with only two temperature sensors and has higher engineering practicability. It is found that the thermal error compensation model of machine tools has a jump interval affected by the ambient temperature. This interval is called the temperature-sensitive interval, and a temperature-sensitive interval subsection point selection algorithm is proposed to build a subsection model on both sides of the segment point. The results show that the Z-direction thermal error of the spindle of CNC machine tools can be basically controlled within 5 μm with only two temperature sensors and that the model is highly robust and has great engineering application value. [ABSTRACT FROM AUTHOR]